- Avinash is an autonomous Industrial engineer with 3+ years of experience as a Data Analyst.
- He is innately curious and immensely passionate about Big Data, Cloud Computing, Business Intelligence, Process improvement, and Project Management.
- Avinash strives to create unqiue end-to-end durable, scalable and available solutions using products and services in the Microsoft Tech stack, providing speed to insights while promoting data integrity.
- He is proficient in utilizing tools such as Power BI, Azure, SQL Server Management Studio, Power Automate and Power Apps.
- Languages: Power Query M, DAX, Python, T-SQL.
Sample Projects
Problem Statement
- Analyze historical sales and profit and territory.
- Identify bestselling products and attributed customers and regions.
- Forecast revenue for the next 7 periods.
- Execute pricing scenario analysis to understand increase in product cost.
Tools : Power BI
Skills: Data Analysis, Data Visualization and Storytelling.
Solution
Here is a video, demonstrating the functionalities below:
- Conditional drilldown using 2 columns: Customer ad Region to analyze Profit.
- Dynamic Product Pricing Scenario Analysis.
- Forecast Revenue for next 7 months+.
- Pareto Chart for Regions and Product Sub Categories. Using the 80-20 Principle to understand best sellers.
- Drill down Territories By Fiscal Year, Customer Details and (Sub)/Product Categories.
- Page Navigation and Custom Filter Panes.
A summary of this project is also available here.
Problem Statement
Multiple linear regression to predict Profit based on Administration spend, Marketing spends, R&D spend and State
Tools: Python.
Skills: Exploratory Data Analysis, Descriptive and Predictive Analysis.
- Importing Libraries such as sklearn,pandas, numpy and matplotlib. Reading csv files.
- Descriptive Analysis ( Exploring avaialble features,null counts and data types, descriptive statistics such as mean, min/max, IQR values.
- Exploratory Data Analysis
- Model Splitting, Training and Testing : Used a 80-20 Split
- Model Evaluation : On tuning the model, the R^2^ Score = 93.47%